There’s no doubt that now is an exciting time for health IT. Many forward-thinking software companies are applying predictive models to create solutions that can improve hospital operations and clinical outcomes. As president and CMO of a Silicon Valley-based healthcare company using data science to improve core processes in healthcare operations, I believe there are a few major elements that health IT companies must incorporate as they continue to evolve to address the needs of our trillion-dollar healthcare system. Here’s what I believe needs to happen in 2019:
An increased emphasis on the patient experience
Practically all health IT companies advertise their dashboards and reporting tools, complete with vast amounts of data. But it’s time to expect more from healthcare software than the mere presentation of data — the data needs to tell a story and result in meaningful process change. Ultimately, the companies that do this successfully will be those that can use empathy to connect data to the patient experience. How are my delays leading to increased patient wait times, and how can I combat the issue? How can we decrease the amount of time it will take for a patient to get scheduled for a procedure? Healthcare IT truly needs companies that can intelligently answer questions like these with their data.
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Solutions that decrease the burden on hospital staff
Surgeon schedulers have to make numerous phone calls back and forth with the OR to get a case scheduled. Nurses are so overloaded with patients in the middle of the day that they are unable to take their lunch breaks. Health IT needs to be deployed in a way that makes life easier for these crucial staff members as opposed to increasing their workload. Whether this is through lightweight solutions that seamlessly integrate with EHRs or digital tools that eliminate the need for manual processes, it’s evident that software in the healthcare space needs to have the interests of those who will use it every day in mind.
Multi-channel engagement
Health IT companies need to understand their targeted user groups and how they function — providers that are constantly on the go may only have time to access capabilities and reports on their phones, for example. The healthcare products that develop the strongest engagement from their users will be those that understand how to leverage different channels (mobile, web, SMS and others) in an effort to reach people in a way that is most convenient for them.
Predictive analytics designed for making things simple
Other digital spaces have been wildly successful in the way they leverage predictive analytics — retail has used targeted advertisements on websites to increase click rates and drive sales, for example. With the massive variety of experiences at both the provider and patient levels, it’s time for healthcare to adopt the same practices. The healthcare IT companies that distance themselves over the next couple years will learn how to analyze data in a way that can improve individuals’ behavior and experiences.
Sophisticated and thoughtful UX and design
While engineering is seen by many as the backbone of software products, many recent Silicon Valley success stories have used elevated design to vault their companies to another level altogether — Airbnb and Slack stand out as notable examples. The time has come for healthcare software to be just as thoughtful in the way that it designs its interfaces to serve the needs of its users. With the amount of resources and value in this industry, there’s no reason that hospitals and patients should have to deal with clunky interfaces. Look for many software companies in the healthcare space to reevaluate how they design their products to create better user experiences.
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Increased leverage of data science to solve some of healthcare’s most difficult problems
With many health IT companies investing significant resources in data science, it’s no surprise that an analytics revolution is already underway. But as companies continue to mine data from hospitals, the most successful ones will begin finding answers to some of healthcare’s biggest issues. For example, how can data science aid in the estimation of case length in order to help hospitals create a more optimized daily schedule and ultimately see more patients on a daily basis?
Photo: klenger, Getty Images
